Comparison of False-Positive Versus True-Positive Findings on Contrast-Enhanced Digital Mammography

Amir, Tali; Hogan, Molly; Jacobs, Stefanie; Sevilimedu, Varadan; Sung, Janice S.; Jochelson, Maxine S.

doi:10.2214/ajr.21.26847

Cited by 15 publications

(1 citation statement)

References 38 publications

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“…For the convenience of referring to these absences and presences, this article will henceforth refer to the confirmed absence of breast cancer as "true negative", and the confirmed presence as "true positive". This nomenclature has been practiced in other recent articles [4].…”

Section: Introductionmentioning

confidence: 99%

Review on Present-day Breast Cancer Detection Techniques

Chan

2024

IJORAS

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Breast cancer remains a prevalent health complication among the female population. Early and reliable detection in an individual is necessary for effective treatment. Thus, R&D into techniques for detection of breast cancer continues to the present. Non-invasive techniques include tactile examinations, electromagnetic scanning and checks for chemical markers. Invasive techniques include biopsies that extract tissue and liquid samples. These techniques have limitations and setbacks that are being addressed with supplementary or complementary techniques. Like the pre-existing techniques, these techniques also rely on comparison of data between control samples and afflicted patients to measure their reliability. Therefore, R&D efforts towards detection of breast cancer have resulted in incremental improvements on established methodologies.

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Section: Introductionmentioning

confidence: 99%

Review on Present-day Breast Cancer Detection Techniques

Chan

2024

IJORAS

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Artificial intelligence computer-aided detection enhances synthesized mammograms: comparison with original digital mammograms alone and in combination with tomosynthesis images in an experimental setting

et al. 2022

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Background It remains unclear whether original full-field digital mammograms (DMs) can be replaced with synthesized mammograms in both screening and diagnostic settings. To compare reader performance of artificial intelligence computer-aided detection synthesized mammograms (AI CAD SMs) with that of DM alone or in combination with digital breast tomosynthesis (DBT) images in an experimental setting. Methods We compared the performance of multireader (n = 4) and reading multicase (n = 388), in 84 cancers, 83 biopsy-proven benign lesions, and 221 normal or benign cases with negative results after 1-year follow-up. Each reading was independently interpreted with four reading modes: DM, AI CAD SM, DM + DBT, and AI CAD SM + DBT. The accuracy of probability of malignancy (POM) and five-category ratings were evaluated using areas under the receiver operating characteristic curve (AUC) in the random-reader analysis. Results The mean AUC values based on POM for DM, AI CAD SM, DM + DBT, and AI CAD SM + DBT were 0.871, 0.902, 0.895, and 0.909, respectively. The mean AUC of AI CAD SM was significantly higher (P = 0.002) than that of DM. For calcification lesions, the sensitivity of SM and DM did not differ significantly (P = 0.204). The mean AUC for AI CAD SM + DBT was higher than that of DM + DBT (P = 0.082). ROC curves based on the five-category ratings showed similar proximity of the overall performance levels. Conclusions AI CAD SM alone was superior to DM alone. Also, AI CAD SM + DBT was superior to DM + DBT but not statistically significant.

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Contrast-enhanced mammography in breast cancer screening

Coffey

Jochelson²

2022

European Journal of Radiology

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Comparison of False-Positive Versus True-Positive Findings on Contrast-Enhanced Digital Mammography

Cited by 15 publications

References 38 publications

Review on Present-day Breast Cancer Detection Techniques

Review on Present-day Breast Cancer Detection Techniques

Artificial intelligence computer-aided detection enhances synthesized mammograms: comparison with original digital mammograms alone and in combination with tomosynthesis images in an experimental setting

Contrast-enhanced mammography in breast cancer screening

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